Federica Ghilardi
- 505206
- Phd: 37th cycle
- Department of Agricultural, Forest and Food Sciences
- Matriculation number: 876642
Contacts
- federica.ghilardi@unito.it
- Dipartimento di Scienze Agrarie, Forestali e Alimentari - DISAFA - Università degli Studi di Torino (Italia). Address: Largo Paolo Braccini 2 - 10095 Grugliasco (TO)
GEO4Agri (Geomatics and Earth Observation for Forestry and Agriculture) - Laboratory of Agro-Forestry Geomatics
- https://phdsustainability.campusnet.unito.it/do/studenti.pl/Show?876642
- VCard contacts
- QRcode contacts
Supervisor
Enrico Corrado Borgogno MondinoCurriculum vitae
Curriculum VitaePhd thesis
Management of vineyards requires local and updated information to optimize yield in a context where climatic and environmental conditions play a focal role. In this framework, the PhD project aims at describing environmental systems behavior spatial and time domains by integrating ground data about soil, water resources, fertilization, and plant protection strategies within agronomic processes with remotely sensed data from satellite/airborne and RPAS (Remotely Piloted Aerial Systems) systems.
A pilot experience will concern the study area that the ongoing SISAV – (Integrated Tools for the Environmental Sustainability of Vineyards) project (https://sisav.org), financed within the PSR-FEASR 2014-2020 Action 16.1 of the Piemonte Region, is focusing on. Results from local tests are expected to be upscaled at worldwide level, taking care of the local environmental and climatic conditions. In particular, transferability will be possibly guaranteed by the global availability of free satellite data and opensource software that are presently accessible for final users.
Satellite data are intended for monitoring, modelling, and forecasting midterm phenomena, since they allow repeated observations of the same area at the global scale. In particular, spectral, geometric and temporal resolutions of the Copernicus Sentinel missions (Sentinel 1 and Sentinel 2) and Landsat are retained to be consistent with environmental systems management requirements. In fact, they are expected to describe those crop dynamics related to its phenology and management, that can be somehow described by proper spectral indices and metrics.
Some additional improvements can come from the recent satellite hyperspectral missions, that can be used to recognize specific chemical/physical elements of vegetation thus improving crop and soil classification, plant physiology description looking for eventual diseases/deforestation events.
Models and procedures designed and calibrated in the pilot area of the SISAV project, will be finally applied to other territorial contexts with special concern about developing countries.